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David Degnan is a biological data scientist who develops bioinformatic and statistical pipelines for multi-omics data, specifically the fields of proteomics, metabolomics, and multi-omics (phenotypic) data integration. He has experience with top-down & bottom-up proteomics analysis, genomics &...

Fusarium sp. DS682 Proteogenomics Statistical Data Analysis of SFA dataset download: 10.25584/KSOmicsFspDS682/1766303 . GitHub Repository Source: https://github.com/lmbramer/Fusarium-sp.-DS-682-Proteogenomics MaxQuant Export Files (txt) Trelliscope Boxplots (jsonp) Fusarium Report (.Rmd, html)...

Washington State University Distinguished Graduate Research Program Program: Chemical Engineering WSU-PNNL Advisor: Aaron Wright

This data is supplementary to the manuscript Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration by Lisa M. Bramer, Holly M. Dixon, David J. Degnan, Diana Rohlman, Julie B. Herbstman, Kim A. Anderson, and Katrina...

Extreme weather events, including fires, heatwaves(HWs), and droughts, have significant impacts on earth, environmental, and power energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning...

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was...

HDF5 file containing 10,000 hydraulic transmissivity inputs and the corresponding hydraulic pressure field outputs for a two-dimensional saturated flow model of the Hanford Site. The inputs are generated by sampling a 1,000-dimensional Kosambi-Karhunen-Loève (KKL) model of the transmissivity field...

This dataset includes one baseline and three cybersecurity based scenarios utilizing the IEEE 9 Bus Model. This instantiation of the IEEE 9 model was built utilizing the OpalRT Simulator ePhasorsim module, with Bus 7 represented by hardware in the loop (HiL). The HiL was represented by two SEL351s...

ProxyTSPRD profiles are collected using NVIDIA Nsight Systems version 2020.3.2.6-87e152c and capture computational patterns from training deep learning-based time-series proxy-applications on four different levels: models (Long short-term Memory and Convolutional Neural Network), DL frameworks...

This dataset includes the results of high-fidelity, hardware in the loop experimentation on simulated models of representative electric and natural gas distribution systems with real cyber attack test cases. Such datasets are extremely important not only in understanding the system behavior during...

Biomedical Resilience & Readiness in Adverse Operating Environments (BRAVE) Project: Exhaled Breath Condensate (EBC) TMT Proteomic Transformation Data Exhaled breath condensate (EBC) represents a low-cost and non-invasive means of examining respiratory health. EBC has been used to discover and...

The Biomedical Resilience & Readiness in Adverse Operating Environments (BRAVE) Project develop new capabilities to improve health and performance of first responders in adverse operating environments common to national defense. The BRAVE project analyze biological samples, collect physiological...
  1. Datasets

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Exhaled breath condensate proteomics represent a low-cost, non-invasive alternative for examining upper respiratory health. EBC has previously been used for the discovery and validation of detected exhaled volatiles and non-volatile biomarkers of disease related to upper respiratory system distress...

This year’s VAST Challenge focuses on visual analytics applications for both large scale situation analysis and cyber security. We have two mini-challenges to test your analytical skills and confound your visual analytics applications. In the first mini-challenge, (the imaginary) BankWorld's largest...

The VAST 2010 Challenge consisted of three mini-challenges (MC) and one Grand Challenge (GC). Each MC had a data set, instructions and a number of questions to be answered. The GC required participants to pull together information from all three data sets and write a debrief summarizing the...